1 citations · 1 across the 7 of their papers we have counts for
7 papers
Automatic Discovery of Disease Subgroups by Contrasting with Healthy Controls
Robin Louiset, Edouard Duchesnay, Benoit Dufumier +2
In biomedical Subgroup Discovery, practitioners are interested in discovering interpretable and homogeneous subgroups within a group of patients. In this paper, assuming that healt…
Weakly Supervised Segmentation and Classification of Alpha-Synuclein Aggregates in Brightfield Midbrain Images
Erwan Dereure, Robin Louiset, Laura Parkkinen +2
Parkinson's disease (PD) is a neurodegenerative disorder associated with the accumulation of misfolded alpha-synuclein aggregates, forming Lewy bodies and neuritic shape used for p…
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset, Edouard Duchesnay, Antoine Grigis +1
Contrastive Analysis is a sub-field of Representation Learning that aims at separating common factors of variation between two datasets, a background (i.e., healthy subjects) and a…
Double InfoGAN for Contrastive Analysis
Florence Carton, Robin Louiset, Pietro Gori
Contrastive Analysis (CA) deals with the discovery of what is common and what is distinctive of a target domain compared to a background one. This is of great interest in many appl…
SepVAE: a contrastive VAE to separate pathological patterns from healthy ones
Robin Louiset, Edouard Duchesnay, Antoine Grigis +2
Contrastive Analysis VAE (CA-VAEs) is a family of Variational auto-encoders (VAEs) that aims at separating the common factors of variation between a background dataset (BG) (i.e.,…
Integrating Prior Knowledge in Contrastive Learning with Kernel
Benoit Dufumier, Carlo Alberto Barbano, Robin Louiset +2
Data augmentation is a crucial component in unsupervised contrastive learning (CL). It determines how positive samples are defined and, ultimately, the quality of the learned repre…
UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised Learning
Robin Louiset, Pietro Gori, Benoit Dufumier +3
Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view,…